AI-IoT-机器人集成：框架、新兴趋势及迈向互联机器人的路径综述
AI-IoT-Robotics Integration: Survey of Frameworks, Emerging Trends, and the Path Toward Connected Robotics
AI总结：
本文综述了人工智能、物联网和机器人三者融合的现状，提出了模块化系统架构，并强调了小语言模型（SLM）和大型语言模型（LLM）在分布式认知与自主决策中的作用，为下一代互联机器人和物理AI生态系统提供了概念和技术路线图。
摘要：
人工智能、物联网和机器人的融合不再是未来的愿景；它正迅速成为实时、智能和上下文感知系统的基础。AI实现感知和推理，IoT提供可扩展的感知和通信，而机器人则提供具身驱动。尽管在AIoT和物联网机器人（IoRT）等两两组合方面取得了显著进展，但仍缺乏完全整合这三者的统一设计框架。本综述综合了这些领域的最新进展，强调了边缘端的小语言模型（SLM）和云端的大型语言模型（LLM）在分布式认知和自主决策中的新兴作用。我们提出了一个符合这些趋势的模块化系统架构，分析了互操作性和反馈控制中存在的持续差距，并根据集成深度对现有工作进行了分类。我们的综述强调了混合SLM-LLM系统与IoT基础设施和机器人代理相结合时，如何应对实时适应、可扩展性和可靠性方面的挑战。这项工作为设计模块化、可解释且能够在动态环境中学习的下一代AI-IoT-机器人生态系统提供了概念和技术路线图，为新兴的互联机器人和物理AI范式铺平了道路。
英文摘要：
The convergence of Artificial Intelligence, the Internet of Things, and Robotics is no longer a futuristic vision; it is rapidly becoming the foundation of real-time, intelligent, and context-aware systems. AI enables perception and reasoning, IoT provides scalable sensing and communication, and robotics delivers embodied actuation. Despite significant progress in pairwise combinations such as AIoT and the Internet of Robotic Things (IoRT), there remains a lack of unified design frameworks that fully integrate all three. This survey synthesizes the state-of-the-art across these domains, emphasizing the emerging role of Small Language Models (SLMs) at the edge and Large Language Models (LLMs) in the cloud for distributed cognition and autonomous decision-making. We propose a modular system architecture that aligns with these trends, analyze persistent gaps in interoperability and feedback control, and classify existing work by integration depth. Our review highlights how hybrid SLM-LLM systems, when coupled with IoT infrastructure and robotic agents, can address challenges in real-time adaptation, scalability, and reliability. This work offers a conceptual and technical roadmap for designing next-generation AI-IoT-Robotic ecosystems that are modular, interpretable, and capable of learning within dynamic environments, paving the way for the emerging paradigm of Connected Robotics and Physical AI.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
